Search

The purpose of this study was to investigate early stage dynamic changes in relevant indicators in neurocritical patients to identify biomarkers that can predict a poor prognosis at an early stage (1–4 days after admission). This study retrospectively collected clinical data, inflammatory indicators, and nutritional indicators from 77 patients at the neurology intensive care unit. The 3-month modified Rankin scale score was used as the outcome indicator. A linear mixed model was used to analyze changes in inflammatory indicators and nutritional indicators in neurocritical patients over time from 1–4 days after admission. Logistic regression was used to determine the independent risk factors for a poor prognosis in neurocritical patients and to construct a predictive model. The predictive efficacy of the model was verified using leave-one-out cross-validation and decision curve analysis methods. The analysis results showed that 1–4 days after admission, the inflammatory indicators of white blood cell and absolute monocyte counts and the nutritional indicators of body cell mass(BCM), fat-free mass, body cell mass/phase angle (BCM/PA), intracellular water, extracellular water, and skeletal muscle index increased overall, while the nutritional indicators of albumin and visceral fat area decreased overall. The logistic multivariate regression model showed that the Charlson comorbidity index (CCI) (odds ratio (OR) = 2.526, 95% CI [1.202, 5.308]), hemoglobin (Hb)(on admission)-Hb(min) (OR = 1.049, 95% CI [1.015, 1.083), BCM(on admission) (OR = 0.794, 95% CI [0.662, 0.952]), and the change in BCM/PA 1–4 days after admission (OR = 1.157, 95% CI [1.070, 1.252]) were independent risk factors for a poor prognosis in neurocritical patients. The predictive analysis showed that the predictive power of Model 1 with BCM/PA (area under the curve (AUC) = 0.95, 95% CI (0.90, 0.99)) was 93%, 65%, 141%, and 133% higher than that of Model 2 without BCM/PA, the CCI, the APACHE II score, and the NRS2002 score (all P < 0.05), respectively. The CCI, Hb(on admission)-Hb(min), BCM(on admission), and an increase in BCM/PA 1–4 days after admission were independently associated with a poor prognosis in neurocritical patients. Of these variables, BCM/PA may be a valid indicator for early stage prediction of a poor prognosis in neurocritical patients. [ABSTRACT FROM AUTHOR]

Rock and soil strength profoundly influences the stability of open-pit mine slopes. Traditional slope design, based on limited drilling data, often disregards inherent uncertainties. Effectively utilizing new sample information from mining operations poses a challenge, hindering dynamic and differentiated design for the entire perimeter slope. To address this, we propose a dynamic optimization method considering rock mass strength uncertainty for the entire perimeter slope. Our approach involves designing slope angles separately in different zones, while thoroughly considering decision-makers' preferences. Furthermore, we delegate the final adjustment authority of slope angles within the safety permissible range to on-site decision-makers. Compared to traditional methods, our dynamic design method incorporates rock mass strength uncertainty into slope evaluation while also accounting for decision-makers' safety and economic preferences. Through a case study of a specific open-pit mine, our proposed dynamic design method increases the overall slope angle by approximately 2.5°, fully accommodating the influence of on-site decision-making preferences on slope design. This article introduces a new method of dynamic optimization of open-pit mine slope based on simplified observation method, which improves the flexibility of decision-making and realizes the differential design of the whole surrounding slope. [ABSTRACT FROM AUTHOR]

Background: The short-term prognosis of stroke patients is mainly influenced by the severity of the primary disease at admission and the trend of disease development during the acute phase (1–7 days after admission). Objective: The aim of this study is to explore the relationship between the bioelectrical impedance analysis (BIA) parameter trajectories during the acute phase of stroke patients and their short-term prognosis, and to investigate the predictive value of the prediction model constructed using BIA parameter trajectories and clinical indicators at admission for short-term prognosis in stroke patients. Methods: A total of 162 stroke patients were prospectively enrolled, and their clinical indicators at admission and BIA parameters during the first 1–7 days of admission were collected. A Group-Based Trajectory Model (GBTM) was employed to identify different subgroups of longitudinal trajectories of BIA parameters during the first 1–7 days of admission in stroke patients. The random forest algorithm was applied to screen BIA parameter trajectories and clinical indicators with predictive value, construct prediction models, and perform model comparisons. The outcome measure was the Modified Rankin Scale (mRS) score at discharge. Results: PA in BIA parameters can be divided into four separate trajectory groups. The incidence of poor prognosis (mRS: 4–6) at discharge was significantly higher in the "Low PA Rapid Decline Group" (85.0%) than in the "High PA Stable Group " (33.3%) and in the "Medium PA Slow Decline Group "(29.5%) (all P < 0.05). In-hospital mortality was the highest in the "Low PA Rapid Decline Group" (60%) compared with the remaining trajectory groups (P < 0.05). Compared with the prediction model with only clinical indicators (Model 1), the prediction model with PA trajectories (Model 2) demonstrated higher predictive accuracy and efficacy. The area under the receiver operating characteristic curve (AUC) of Model 2 was 0.909 [95% CI 0.863, 0.956], integrated discrimination improvement index (IDI), 0.035 (P < 0.001), and net reclassification improvement (NRI), 0.175 (P = 0.031). Conclusion: PA trajectories during the first 1–7 days of admission are associated with the short-term prognosis of stroke patients. PA trajectories have additional value in predicting the short-term prognosis of stroke patients. [ABSTRACT FROM AUTHOR]

The active wave absorption method has been widely employed in numerical wave tanks. The wave absorption performance of active wave absorption methods is investigated within a numerical wave tank based on a lattice Boltzmann method. Specifically, two active wave absorption methods—the classical shallow water method and the extended range method—are compared. By analyzing the contributions of free and bound components in the harmonics of the reflected wave to the reflection coefficient, we found that the extended-range method is more effective than the shallow-water method in absorbing the reflection of the primary harmonic. Moreover, a wave absorption performance index is proposed to carry out rapid evaluation of active wave absorption method performance without resorting to numerical simulations. Our findings indicate that the performance index ratio of two active wave absorption methods closely mirrored their reflection coefficient ratio. Notably, the extended-range method significantly reduces the performance index in both shallow and deep waters, exhibiting superior active absorption performance within the lattice Boltzmann method-based numerical wave tank context compared to the shallow-water method. [ABSTRACT FROM AUTHOR]

As mechanized open-pit coal mining intensifies, assessing and predicting slope stability has become increasingly important. To address the limitations of traditional mechanical calculations, numerical simulations, and physical experiments, this paper identifies the key factors impacting slope stability in open-pit mines and develops a multi-parameter sample data set. The study employs hyperparameters optimized using a Bayesian algorithm, introduces additional convolutional layers, and combines the Adam optimizer with dropout techniques to enhance the feature extraction and performance of one-dimensional convolutional neural networks (1D-CNN). This leads to a Bayesian-optimized one-dimensional convolutional neural network (B-1D MCNN) model for predicting slope stability.The study evaluates the classification performance and accuracy of various models for slope stability, including BP neural networks, genetic algorithm-optimized convolutional neural networks, 1D-CNN, and B-1D MCNN, using accuracy, precision, and F1-score as metrics. The analysis also examines the influence of factor indicators and training set length on the model's output to assess its generalization capabilities.The research findings suggest that: (1) the B-1D MCNN model for evaluating slope stability demonstrates the capability to accurately depict the nonlinear correlation between influencing factors and slope stability. (2) Compared with other models, the B-1D MCNN model has shown enhancements of 10.96% to 27.85%, 10.26% to 28.55%, and 8.98% to 25.05% in terms of Accuracy, F1-Score, and Precision, respectively. (3) As the length of the training dataset increases, the performance of the model improves accordingly. (4) The B-1D MCNN model shows a generalization power of 87.5%. [ABSTRACT FROM AUTHOR]

The production plan of an open-pit mine depends on the block model, so it's crucial to determine the appropriate method and size for partitioning it. This study proposes a new method based on a closed shell three-dimensional geological model for determining block model size in open-pit mines. Instead of using regular block models, the shell model is directly cut, and the discrete geological body is referred to as the "mining model." Mining parameters and the shovel-truck's performance are integrated into the method. Bench height determines the Z-axis size, bench slope angle determines the inclination angle, and shovel width determines the X-axis size of the block model. The operation efficiency of the shovel-truck considers the probability distribution of simultaneous operations, allowing the determination of the Y-axis size of block models for different types of shovels. The developed "Mining Model" module in the software "Life Cycle Mining System" is used for practical implementation. By comparing the results with traditional block models, the superiority of the proposed method is demonstrated. This study provides a more accurate model for optimizing the production plan of open-pit mines throughout their life cycle. [ABSTRACT FROM AUTHOR]

In this study, Setaria viridis was selected as the research object, the soil reinforcement mode of roots was analyzed, and the general mechanical model of soil reinforcement was proposed. The direct shear tests of root–soil composite and root tensile tests were carried out, and the relationship between the root additional cohesion and root depth was studied. Furthermore, numerical simulations were established to explore the variation law of shallow displacement and slope stability as a function of the root ratio. The results show that the effect of herbaceous plant roots on the soil was composed of material modification and root binding force on the soil. The shear strength improvement of the root–soil composite was mainly reflected by the increase in cohesion. Furthermore, the composite cohesion was positively correlated with the root content but negatively correlated with the water content. With the increase in root diameter, the tensile strength of the Setaria viridis root increased linearly, but its tensile strength decreased and showed a power relation. The greater the total cohesion of the root–soil composite layer, the smaller the total displacement and the higher the slope stability. Thus, the slope's herbaceous vegetation could effectively control the deformation and slip of the shallow soil, which has good application value for reducing soil erosion in mining areas. [ABSTRACT FROM AUTHOR]

This paper presents simulations of flow past a circular cylinder within the subcritical Reynolds number (Re) range from 3900 to 2 × 105, utilizing the parameterized cumulant lattice Boltzmann model. In this study, a three-dimensional characteristic boundary condition for incompressible flow has been integrated into the lattice Boltzmann method at the outflow boundary to minimize spurious reflection. The flow field, wake statistics, hydrodynamic force, and power spectra results of Re = 3900 from the cumulant lattice Boltzmann model are exhaustively compared with the laboratory data and other numerical models. Relative to other numerical models employing turbulence closure, the cumulant lattice Boltzmann simulations demonstrate enhanced agreement with the experimental data even with relatively coarser grid resolution. The resolution-spanning feature for the cumulant lattice Boltzmann model in turbulent flows, without using explicit turbulence model, aligns with the previous benchmark case studies. The stability-preserving regularization process in the present model is analyzed. Results indicate that the influence of the regularization parameter is mitigated with improved grid resolution. A specific regularization parameter for flow around cylinder simulations is recommended. Variations in flow properties and hydrodynamic forces within the subcritical Reynolds number range of 3900 to 2 × 105 are analyzed. The results confirm that the parameterized cumulant lattice Boltzmann model can accurately simulate practical engineering flows, characterized by complex separation and recirculation, within the subcritical range. Moreover, the computational efficiency and parallel scalability are compared with other numerical methods. [ABSTRACT FROM AUTHOR]

The objective principles of shiology are mainly reflected in three fields as food acquisition, eaters' health and shiance order. Most of the objective principles in the field of food acquisition have been revealed by agronomy and foodstuff science. This research mainly focuses on 10 principles in the field of eaters' health and shiance order and in addition, there are also five lemmas that extend from the above principles. The 10 principles are the core theory of the shiology knowledge system, which play an important role in the objective principles revealed by human beings and constitute one of the basic principles of human civilization. Compared with the scientific principles of mathematics, physics, chemistry and economics, the principles of shiology have three characteristics as popularity, practicability and survivability. The principles of shiology in the field of eaters' health are all around us, and everyone can understand and master them. Using the principles of shiology can improve the healthy life span of 8 billion people. The principles of shiology in the field of shiance order is an important tool of social governance, which can reduce human social conflicts, reduce social involution, improve overall efficiency of social operation, and maintain the sustainable development of human beings. [ABSTRACT FROM AUTHOR]

Neutrophil extracellular trap (NET) is one of the defense functions of neutrophils, which has a rapid ability to kill infections and is also crucial in a variety of immune‐associated diseases including infections, tumors and autoimmune diseases. Recent studies have shown that NETs are closely related to the development of tumors. The regulatory role of NETs in tumors has been of interest to researchers. In addition to awakening latent tumor cells, NETs can also promote the proliferation and development of tumor cells and their metastasis to other sites. At the same time, NETs also have the effect of inhibiting tumors. At present, there are some new advances in the impact of NETs on tumor development, which will provide a more theoretical basis for developing NET‐targeted drugs. Therefore, this review just summarized the formation process of NETs, the regulation of tumor development and the treatment methods based on NETs. [ABSTRACT FROM AUTHOR]

The delineation of the open-pit mining boundary, particularly in the context of medium to long-term planning, forms the foundation of mining design. However, due to the non-linear and dynamic nature of the economic and technical parameters influencing boundary delineation, determining the optimal mining boundary can be exceedingly challenging. Currently, most boundary optimization methods assume that block parameters remain fixed, which results in enterprises assuming a certain level of risk when facing changes in internal and external conditions. In this regard, this paper introduces the concept of "achievement degree" to reflect the risk associated with the results of boundary design. Using coal prices as an example, this article applies the predicted coal price curve to boundary optimization adjustments by specifying the "achievement degree" requirements for various time periods, thereby facilitating risk-controlled and economically optimal boundary decisions. Taking the illustrative case of an idealized small-scale inclined coal seam open-pit mine, adjustments to the boundary closely track variations in coal prices, further enhancing returns. The results demonstrate that the method proposed in this paper can increase overall revenue by approximately 51.15% within the forecast period, while effectively managing risks. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Research on the method of determining the block size for an open-pit mine integrating mining parameters and shovel-truck's operation efficiency." The original article contained an error in the Acknowledgements section, specifically the grant number for the National Natural Science Foundation of China. The corrected version of the article acknowledges the correct grant number. The authors of the article are Weiqiang Guo, Guangwei Liu, Jiaming Li, Senlin Chai, and Shupeng Guo. [Extracted from the article]

Objective: Observational studies have revealed a link between inflammatory bowel disease (IBD) and sarcopenia. However, it remains unclear whether this correlation between IBD and sarcopenia is causal., Methods: The genetic instrumental variables (IVs) associated with IBD and sarcopenia-related traits were derived from publicly available genome-wide association studies. We employed a two-sample bidirectional Mendelian randomization (MR) method. we obtained genetic IVs for five phenotypes from 34,652 cases in IBD, 27,432 cases in ulcerative colitis (UC), 212356 cases in crohn's disease (CD), 9336415 cases in low hand grip strength (LHGS), and 450243 cases in appendicular lean mass (ALM), respectively. The inverse variance weighting and other MR methods were used to explore the bidirectional causal relationship. Furthermore, we performed heterogeneity test, pleiotropy test, leave-one-out sensitivity test, and multivariate MR to evaluate the robustness of the results., Results: The forward MR results showed that the UC (OR=0.994, 95% CI: 0.9876-0.9998, P = 0.044) and CD (OR=0.993, 95% CI: 0.988-0.998, P = 0.006) was negatively correlated with ALM. In the reverse MR analysis, we also found that LHGS was negatively correlated with the IBD (OR=0.76, 95% CI: 0.61-0.94, P = 0.012) and CD (OR=0.53, 95% CI: 0.40-0.70, P <0.001). Besides, genetically predicted higher ALM reduced IBD (OR=0.87, 95% CI: 0.79-0.95, P = 0.002), UC (OR=0.84, 95% CI: 0.76-0.93, P = 0.001), and CD (OR=0.87, 95% CI: 0.77-0.99, P = 0.029). However, the results of other MR Analyses were not statistically different., Conclusions: We found genetically predicted UC and CD are causally associated with reduced ALM, and higher hand grip strength reduced IBD and CD risk, and higher ALM reduced IBDs risk. This MR study provides moderate evidence for a bidirectional causal relationship between IBD and sarcopenia., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Sun, Liu, Xu, Zhang, Wei, Wu and Jiang.)